Visual performance testing presents a number of challenges. While visual function is currently assessed in clinical and research settings by objective measurements (e.g., visual acuity testing, contrast sensitivity testing), these measurements do not always provide an accurate indication of subjects' visual function in a practical sense. One drawback of these methods is that they typically test only one or two aspects of vision at a time (target size, percent contrast). Real world visual function consists of responding based on multiple characteristics of a visual target (e.g., size, percent contrast, motion or speed, color, etc.). Even if multiple visual tests are performed, each test is tailored to the specific aspect that it measures, so that a holistic sense of visual performance is not obtained.
Even existing tests that attempt to evaluate visual function using representative activities of daily life have shortcomings. An example is testing visual performance using a driving simulator. The complexity of the apparatus often makes testing expensive, requiring subjects to travel to a particular location which can be remote from their physician's office. Additionally, the testing experience often includes tasks requiring more complex cognitive and physical function than simply vision. For example, in some driving simulators subjects must literally sit behind the wheel/windshield and operate controls in response to stimuli—this requires the coordination of visual processing and physical responses. Thus this testing scenario does not achieve a pure assessment of visual function.
Based on the available tests, there remains a need for visual performance measurement that is more consistent with real world function.